Estimation of parameters and unobserved components for nonlinear systems from noisy time series
- We study the problem of simultaneous estimation of parameters and unobserved states from noisy data of nonlinear time-continuous systems, including the case of additive stochastic forcing. We propose a solution by adapting the recently developed statistical method of unscented Kalman filtering to this problem. Due to its recursive and derivative-free structure, this method minimizes the cost function in a computationally efficient and robust way. It is found that parameters as well as unobserved components can be estimated with high accuracy, including confidence bands, from heavily noise-corrupted data.
| Verfasserangaben: | Andre Sitz, Udo Schwarz, Jürgen KurthsORCiDGND, Henning U. Voss |
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| URL: | http://pre.aps.org/ |
| Publikationstyp: | Wissenschaftlicher Artikel |
| Sprache: | Englisch |
| Jahr der Erstveröffentlichung: | 2002 |
| Erscheinungsjahr: | 2002 |
| Datum der Freischaltung: | 24.03.2017 |
| Quelle: | Physical Review / E. - 66 (2002), S. 016210 |
| Organisationseinheiten: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Physik und Astronomie |
| Name der Einrichtung zum Zeitpunkt der Publikation: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Physik |
